Early-career healthcare roles provide essential experience for staff to build professional judgement and understanding of how our services work. However, as AI takes on time-consuming administrative burdens – such as coordinating appointments, preparing reports, and resolving queries – we need to ensure that valuable learning is not removed with it. To realise the potential of non-clinical AI for the healthcare workforce, it is vital that we consider how it can be used as a tool for building foundational skills, confidence, and digital literacy. 

In the Health Innovation Network South London’s (HIN) report, Beyond productivity: AI and NHS workforce implications, we highlight how AI can redistribute work, and support skill development. Non-clinical AI provides opportunities to design new ways for junior staff to build the experience required to progress into specialist and management roles. If junior staff cannot gain core competencies, knowledge, and experience through administrative work that becomes automated by AI organisations may lose out on a strong talent pipeline in the years ahead. One of the report’s key recommendations for future-proofing the workforce is in “ensuring that AI adoption supports, rather than disrupts, career development”. It is more crucial than ever to protect career development pathways for the long-term resilience of the wider workforce.  

AI has the potential to support staff to combine practical experience with more personalised opportunities to learn. AI-supported simulation, for example, could allow staff to practise unfamiliar situations, try different approaches and receive feedback before applying their learning at work. For instance, a new administrator might rehearse a conversation with an anxious patient about a delayed appointment, while an aspiring manager could explore competing staffing priorities and discuss their reasoning with a supervisor.  

Innovators we work with at the HIN are already demonstrating this potential. Upskill.Health, an alumnus of Accelerating FemTech, develops AI-powered roleplay to support maternity staff to improve their communication skills for critical care. Elsewhere, London Ambulance Service has piloted using Ambient Voice Technology and AI training stimulation for emergency call taker training, working with DigitalHealth.London Accelerator alumni Tortus and KAIWA respectively.  

Even before talent reaches the front-line, AI can help to build the core skills that are needed to sustain the healthcare workforce. At Great Western Hospitals NHS Foundation Trust, medical students use AI virtual patients to practise communication and clinical decision-making alongside teaching and placements, including challenging conversations about consent and vaccine hesitancy. Researchers at the National University of Singapore have also tested AI-supported virtual reality for nursing students’ team communication and sepsis training, offering another example of how technology can support learning alongside face-to-face simulation. 

Although these examples focus on clinical learners, they provide a starting point for how solutions could benefit administrative and operational staff. Simulation could sit alongside mentoring, shadowing, and supervised responsibility, while some of the time released through automation could – with the support of senior leaders – be reinvested in personal development. This would help staff build confidence in using AI while strengthening the interpersonal skills, service knowledge, and judgement they need as their careers progress. 

Achieving this will require realistic scenarios, meaningful feedback, and human supervision, along with access that extends across roles and levels of digital confidence. Involvement and co-design with junior colleagues should shape these products too, so that learning reflects the situations they encounter, including where AI changes their work without them using it directly. It will also require system leadership that prioritises sustainability; productivity improvements from AI will quickly evaporate if our future workforce lacks the foundational skillset to supervise it. 

For the HIN and our partners, this presents an opportunity to connect innovation with workforce development by bringing services, educators, technology developers, and staff together to test approaches and share learning. Alongside productivity, we should assess whether AI helps people develop skills, take on meaningful responsibility, and progress in their careers. By building learning into adoption from the outset, we can support better services today while developing the experienced workforce and leaders that healthcare will need tomorrow.